9780470743614-0470743611-Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms

ISBN-13: 9780470743614
ISBN-10: 0470743611
Edition: 1
Author: Kalyanmoy Deb
Publication date: 2009
Publisher: Wiley
Format: Paperback 544 pages
Category: Engineering
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Book details

ISBN-13: 9780470743614
ISBN-10: 0470743611
Edition: 1
Author: Kalyanmoy Deb
Publication date: 2009
Publisher: Wiley
Format: Paperback 544 pages
Category: Engineering

Summary

Multi-Objective Optimization Using Evolutionary Algorithms (ISBN-13: 9780470743614 and ISBN-10: 0470743611), written by authors Kalyanmoy Deb, was published by Wiley in 2009. With an overall rating of 4.4 stars, it's a notable title among other Engineering books. You can easily purchase or rent Multi-Objective Optimization Using Evolutionary Algorithms (Paperback) from BooksRun, along with many other new and used Engineering books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $1.02.

Description

The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists.

Evolutionary algorithms are very powerful techniques used to find solutions to real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run.

  1. Comrephensive coverage of this growing area of research.
  2. Carefully introduces each algorithm with examples and in-depth discussion.
  3. Includes many applications to real-world problems, including engineering design and scheduling.
  4. Includes discussion of advanced topics and future research.
  5. Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms

Provides an extensive discussion on the principles of multi-objective optimization and on a number of classical approaches.

This integrated presentation of theory, algorithms and examples will benefit those working in the areas of optimization, optimal design and evolutionary computing.

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